Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "79"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 79 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 33 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 33 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 79, Node N11:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2460016 not_connected 100.00% 0.00% 100.00% 0.00% - - 0.729058 15.185868 -0.984119 5.622775 -0.712731 6.485787 0.633208 -0.023315 0.5377 0.0399 0.4350 nan nan
2460015 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.045406 15.599369 -0.939766 5.901694 -0.347107 6.912966 0.053611 -0.214201 0.5486 0.0409 0.4403 nan nan
2460014 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.236838 13.332017 -0.999071 4.049561 -0.986117 10.354910 1.639986 -0.506663 0.5141 0.0384 0.4187 nan nan
2460013 not_connected 100.00% 0.00% 100.00% 0.00% - - 0.752893 15.616667 -0.954224 5.843130 -0.340238 6.895142 0.388337 0.120388 0.5431 0.0397 0.4391 nan nan
2460012 not_connected 100.00% 0.00% 100.00% 0.00% - - 0.763566 14.661583 -1.141274 5.674534 -0.628033 7.613648 0.078748 0.069218 0.5474 0.0411 0.4365 nan nan
2460011 not_connected 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2460010 not_connected 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2460009 not_connected 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan 0.0232 0.0797 -0.0197 nan nan
2460008 not_connected 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2460007 not_connected 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2459999 not_connected 0.00% 0.08% 99.92% 0.00% - - nan nan nan nan nan nan nan nan 0.5439 0.0348 0.2544 nan nan
2459998 not_connected 100.00% 0.00% 100.00% 0.00% - - 0.691987 12.343692 -1.038521 4.973784 -1.039275 10.043037 0.815757 0.180164 0.5736 0.0390 0.4552 nan nan
2459997 not_connected 100.00% 0.00% 100.00% 0.00% - - 0.688675 13.442813 -1.135354 5.427643 -1.153799 9.487067 0.775967 0.022349 0.5919 0.0413 0.4627 nan nan
2459996 not_connected 100.00% 98.86% 98.92% 0.00% - - 246.486238 246.684330 inf inf 3071.133829 3126.405062 4157.081471 4426.729752 0.4814 0.4681 0.4578 nan nan
2459995 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.315905 14.724254 -1.408237 6.147857 -0.854635 9.301369 1.311805 -0.129340 0.5867 0.0445 0.4456 nan nan
2459994 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.373814 14.302254 -1.232283 5.353481 -0.709628 9.451715 1.241890 0.675751 0.5809 0.0403 0.4454 nan nan
2459993 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.921483 13.480184 -1.317146 4.681296 -0.489925 10.783950 0.427817 1.122468 0.5728 0.0339 0.4411 nan nan
2459991 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.853950 16.696899 -1.295046 5.093615 -0.651203 10.636299 0.722917 -0.575496 0.5814 0.0387 0.4556 nan nan
2459990 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.478094 13.756709 -1.273414 4.842157 -0.671100 10.932457 0.783454 -0.705597 0.5742 0.0423 0.4440 nan nan
2459989 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.003130 13.945630 -1.084713 4.540740 -0.891657 9.154867 0.399478 -0.702785 0.5751 0.0384 0.4494 nan nan
2459988 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.389190 16.320047 -1.424697 4.916266 -0.816814 13.077813 0.576607 -0.635272 0.5801 0.0381 0.4536 nan nan
2459987 not_connected 100.00% 0.00% 100.00% 0.00% - - 0.808813 13.639893 -1.357269 5.074069 -1.009814 7.884074 -0.276962 -0.070507 0.5890 0.0408 0.4609 nan nan
2459986 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.611884 16.718774 -1.449967 5.401132 -1.072085 11.130030 -0.188798 8.757909 0.6097 0.0399 0.4608 nan nan
2459985 not_connected 100.00% 0.00% 100.00% 0.00% - - 0.351295 15.117791 -0.730804 5.099831 -1.167786 8.499671 -0.598951 -0.383588 0.6000 0.0404 0.4705 nan nan
2459984 not_connected 100.00% 0.00% 100.00% 0.00% - - 0.144726 14.490447 -0.672347 5.381731 -0.918269 12.035968 -0.928425 1.587933 0.6153 0.0426 0.4698 nan nan
2459983 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.582136 14.262065 -1.316623 4.857571 -0.968723 11.036876 0.357028 5.165544 0.6243 0.0407 0.4418 nan nan
2459982 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.465013 11.763010 -0.845381 4.321985 -0.979857 5.192966 0.042444 3.059887 0.6571 0.0393 0.4849 nan nan
2459981 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.706058 13.163846 -1.486450 4.989044 -0.379660 12.233403 0.839476 -0.639143 0.5831 0.0415 0.4529 nan nan
2459980 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.397034 12.754952 -1.483894 4.667798 -0.769445 10.665857 -0.770413 4.958689 0.6281 0.0411 0.4702 nan nan
2459979 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.867213 13.253018 -1.464825 4.240531 -0.574157 10.015000 0.868844 -0.382447 0.5764 0.0395 0.4484 nan nan
2459978 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.683964 13.469519 -1.508705 4.560337 -0.569887 10.842042 1.191920 -0.880226 0.5765 0.0373 0.4593 nan nan
2459977 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.579895 14.187489 -1.431015 4.724064 0.304933 11.209013 0.926222 0.018478 0.5454 0.0420 0.4163 nan nan
2459976 not_connected 100.00% 0.00% 100.00% 0.00% - - 1.940177 13.686622 -1.525976 4.743853 -0.580162 10.707254 1.295964 -0.093902 0.5853 0.0387 0.4619 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 79: 2460016

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 15.185868 15.185868 0.729058 5.622775 -0.984119 6.485787 -0.712731 -0.023315 0.633208

Antenna 79: 2460015

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 15.599369 15.599369 1.045406 5.901694 -0.939766 6.912966 -0.347107 -0.214201 0.053611

Antenna 79: 2460014

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 13.332017 1.236838 13.332017 -0.999071 4.049561 -0.986117 10.354910 1.639986 -0.506663

Antenna 79: 2460013

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 15.616667 0.752893 15.616667 -0.954224 5.843130 -0.340238 6.895142 0.388337 0.120388

Antenna 79: 2460012

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 14.661583 0.763566 14.661583 -1.141274 5.674534 -0.628033 7.613648 0.078748 0.069218

Antenna 79: 2460011

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected ee Shape nan nan nan inf inf nan nan nan nan

Antenna 79: 2460010

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected ee Shape nan nan nan inf inf nan nan nan nan

Antenna 79: 2460009

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected ee Shape nan nan nan inf inf nan nan nan nan

Antenna 79: 2460008

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape nan nan nan inf inf nan nan nan nan

Antenna 79: 2460007

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected ee Shape nan nan nan inf inf nan nan nan nan

Antenna 79: 2459999

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape nan nan nan nan nan nan nan nan nan

Antenna 79: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 12.343692 0.691987 12.343692 -1.038521 4.973784 -1.039275 10.043037 0.815757 0.180164

Antenna 79: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 13.442813 0.688675 13.442813 -1.135354 5.427643 -1.153799 9.487067 0.775967 0.022349

Antenna 79: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected ee Power inf 246.486238 246.684330 inf inf 3071.133829 3126.405062 4157.081471 4426.729752

Antenna 79: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 14.724254 1.315905 14.724254 -1.408237 6.147857 -0.854635 9.301369 1.311805 -0.129340

Antenna 79: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 14.302254 1.373814 14.302254 -1.232283 5.353481 -0.709628 9.451715 1.241890 0.675751

Antenna 79: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 13.480184 1.921483 13.480184 -1.317146 4.681296 -0.489925 10.783950 0.427817 1.122468

Antenna 79: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 16.696899 1.853950 16.696899 -1.295046 5.093615 -0.651203 10.636299 0.722917 -0.575496

Antenna 79: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 13.756709 13.756709 1.478094 4.842157 -1.273414 10.932457 -0.671100 -0.705597 0.783454

Antenna 79: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 13.945630 13.945630 1.003130 4.540740 -1.084713 9.154867 -0.891657 -0.702785 0.399478

Antenna 79: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 16.320047 16.320047 1.389190 4.916266 -1.424697 13.077813 -0.816814 -0.635272 0.576607

Antenna 79: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 13.639893 0.808813 13.639893 -1.357269 5.074069 -1.009814 7.884074 -0.276962 -0.070507

Antenna 79: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 16.718774 16.718774 1.611884 5.401132 -1.449967 11.130030 -1.072085 8.757909 -0.188798

Antenna 79: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 15.117791 15.117791 0.351295 5.099831 -0.730804 8.499671 -1.167786 -0.383588 -0.598951

Antenna 79: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 14.490447 0.144726 14.490447 -0.672347 5.381731 -0.918269 12.035968 -0.928425 1.587933

Antenna 79: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 14.262065 1.582136 14.262065 -1.316623 4.857571 -0.968723 11.036876 0.357028 5.165544

Antenna 79: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 11.763010 1.465013 11.763010 -0.845381 4.321985 -0.979857 5.192966 0.042444 3.059887

Antenna 79: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 13.163846 13.163846 1.706058 4.989044 -1.486450 12.233403 -0.379660 -0.639143 0.839476

Antenna 79: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 12.754952 12.754952 1.397034 4.667798 -1.483894 10.665857 -0.769445 4.958689 -0.770413

Antenna 79: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 13.253018 1.867213 13.253018 -1.464825 4.240531 -0.574157 10.015000 0.868844 -0.382447

Antenna 79: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 13.469519 13.469519 1.683964 4.560337 -1.508705 10.842042 -0.569887 -0.880226 1.191920

Antenna 79: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 14.187489 1.579895 14.187489 -1.431015 4.724064 0.304933 11.209013 0.926222 0.018478

Antenna 79: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
79 N11 not_connected nn Shape 13.686622 13.686622 1.940177 4.743853 -1.525976 10.707254 -0.580162 -0.093902 1.295964
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